In: Statistics and Probability
Up to this point, the data analysis procedures you have been learning about have all assumed a normal distribution of the population. However, there are times when the distribution of a population is not normal, at which time you will need to choose a different analysis strategy. What are two to three examples of populations that are not normally distributed?
Examples of non-normal populations:
1. A population containing the number of phone calls arriving at a certain call center within a minute follows a Poisson distribution. This example was cited by A.K. Erlang (1878 – 1929).
2. The time, taken by radioactive particles for decaying follows an Exponential distribution approximately instead of following normal. Hence such a population will be non-normal.
3. The distribution of wealth in society follows a Pareto distribution. Vilfredo Pareto originally used this distribution to describe the allocation of wealth among individuals since it seemed to show rather well the way that a larger portion of the wealth of any society is owned by a smaller percentage of the people in that society. He also used it to describe the distribution of income. This idea is sometimes expressed more simply as the Pareto principle or the "80-20 rule" which says that 20% of the population controls 80% of the wealth. Hence the population of income is non-normal.